Risk and resilience in autism spectrum disorder: a missed translational opportunity?
Bibliographic record
Abstract
The objective of this review is to provide a narrative summary of risk and resiliency in autism spectrum disorder (ASD) over the lifespan. In recent years, much has been learned about risk factors for ASD which include both genetic and environmental mechanisms. Resiliency in ASD is much less studied but examples can be gleaned by exploring studies that allow for heterogeneity in causation and outcome. Possible examples come from the literature on sex difference, infant siblings, and natural history. Exciting translational opportunities can be achieved through a greater focus on understanding protective factors and resiliency in ASD than the field's almost exclusive focus on risk factors and the ability to predict poor outcomes. Although the exact nature of processes that protect in ASD are not yet known, putting a resiliency lens on research and clinical practice may prove illuminating. WHAT THIS PAPER ADDS: Resiliency in autism spectrum disorder is a function of the vast variation seen in etiology and outcome. A focus on strengthening protective factors may improve long-term outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".